38 datasets found

A 2-dimensional toy dataset used to illustrate the performance-interpretability dilemma in single-subject decoding.

The dataset used in the paper Neural 3D Mesh Renderer. The dataset consists of 3D models of objects.

The Cap3D dataset is a large-scale dataset of 3D models with captions.

The Objaverse-LVIS dataset contains ∼ 46,000 3D models in 1,156 categories.

The Pix3D dataset is a dataset of pairs of natural images and CAD models.

Text-to-Mesh is a dataset of 3D models generated from text prompts.

Text2Mesh is a dataset of 3D models generated from text prompts.

The SHREC ’11 dataset is a popular choice for evaluating network performance in shape classification tasks.

Shapenet is a large-scale synthesis 3D object dataset, where we follow [9] to use the official test splits of chair, car, and motorbike categories for evaluation since they...

The ICCV dataset is a benchmark for learning deep object detectors from 3D models.

Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen...

The Pix3D dataset is a collection of 3D models with RGB images, used for training and testing 3D object recognition and generation tasks.

3D Convolutional Neural Networks are sensitive to transformations applied to their input. This is a problem because a voxelized version of a 3D object, and its rotated clone,...

The Pacific Graphics 2022 dataset is a collection of 3D models used for point cloud completion tasks.

ShapeNet-Part dataset consists of 16881 3D objects, covering 16 shape categories. Most of the point cloud instances are annotated with less than six part labels, and there exist...

The dataset used in the paper is ShapeNetPart, a synthetic dataset for 3D object part segmentation. It contains 16,881 models from 16 categories.

The ShapeNetCore dataset is a large-scale 3D model dataset, containing 44,000 3D models and 13 categories.

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...